Motorized vehicles (e.g., automobiles) become popular in the daily life. In additional to the constant progress in perspectives of power, driving safety requirements for automobiles are becoming higher.
A driver usually identifies other objects in front and/or next to his/her automobile with his/her naked eye. To enhance safety, a forward-looking safety warning system installed in an automobile is available. The forward-looking safety warning system, generally installed behind a windshield in the front of an automobile, captures images in front of the automobile and identifies obstacles in the images, so as to remind the driver to keep a safety distance or to prevent the driver from dangerous driving behaviors. However, in adverse weather conditions such as rainstorms, the recognition rate of the forward-looking safety warning system may be significantly degraded. Periodic noise pixels (e.g., wiper objects swinging back and forth) in the images may partially or periodically block recognition targets (e.g., pedestrians, automobiles, traffic signs) of the forward-looking safety warning system. Consequently, the forward-looking safety warning system may make a misjudgment, implying that the driver driving under such circumstances may be dangerous.
Although a technique for determining if image is influenced by rain is available, there is no technique capable of determining whether periodic noise pixels (e.g., wiper objects) are present in the images and determining whether to filter out the periodic noises. Although a rain streak elimination method was proposed, it is inapplicable to the forward-looking safety warning system. A main reason is that, removing of rain streaks in the images is less significant than removing wiper objects in the images. A solution for clarifying foggy images was also proposed. Nonetheless, as wipers are considered as the most significant noise source once they are activated, such solution is also not capable of removing the interference coming from wipers.